library(dplyr)
library(data.table)
library(ggmap)
library(ggplot2)

fread("NYPD_Complaint_Data_Historic.csv",na.strings="",colClasses = c(PARKS_NM="c",HADEVELOPT="c"),nrows = 15000, stringsAsFactors = TRUE)->df

Basic Data Mnupulation

df$CMPLNT_FR_DT <- as.Date(df$CMPLNT_FR_DT, format='%m/%d/%Y')
df$crime_year <- year(df$CMPLNT_FR_DT)
#df$crime_year 

#View(df)
#levels(factor(df$crime_year))
#str(df)


#Bronx Data
dfBronx<- filter(df,df$BORO_NM== "BRONX")
#View(dfBronx)

#Quens Data
dfQUEENS<- filter(df,df$BORO_NM== "QUEENS")
#View(dfBronx)

#Manhatten Data
dfManhattan<- filter(df,df$BORO_NM== "MANHATTAN")
#Brooklyn Data
dfBrooklyn<- filter(df,df$BORO_NM== "BROOKLYN")

#STATEN ISLAND Data
dfSTIsland<- filter(df,df$BORO_NM== "STATEN ISLAND")
#View(dfBronx)

NewYork <- get_map(location = "new york city",  color = "bw",
                zoom = 11, maptype = "toner", source = "google")

Genral NYC Map

set.seed(12)
ggmap(NewYork)

NYC Map Overal Crime Types

ggplot()+geom_point(data = df, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Crime analysis for Bronx

ggplot()+geom_polygon(data=dfBronx,aes(x = Longitude, y = Latitude))+
geom_point(data = dfBronx, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Crime analysis for Queens

ggplot()+geom_polygon(data=dfQUEENS,aes(x = Longitude, y = Latitude))+
geom_point(data = dfQUEENS, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Crime analysis for Manhattan

ggplot()+geom_polygon(data=dfManhattan,aes(x = Longitude, y = Latitude))+
geom_point(data = dfManhattan, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Crime analysis for Brooklyn

ggplot()+geom_polygon(data=dfBrooklyn,aes(x = Longitude, y = Latitude))+
geom_point(data = dfBrooklyn, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Crime analysis for Staten Island

ggplot()+geom_polygon(data=dfSTIsland,aes(x = Longitude, y = Latitude))+
geom_point(data = dfSTIsland, aes(x = Longitude, y = Latitude ,colour = factor(LAW_CAT_CD))) +theme(legend.position = "top")

Overal Crime data view

ggmap(NewYork) +
geom_point(data = df, aes(x = Longitude, y = Latitude,colour = factor(LAW_CAT_CD)))+ scale_colour_manual(values = rainbow(14)) + labs(x = "Longitude", y = "Latitude", title = "Map of NYC with the borough boundaries")+theme(legend.position = "top")

#+facet_wrap(~crime_year,ncol = 2)

Crime High density regions

ggmap(NewYork) +
  stat_density2d(aes(x = Longitude, y = Latitude, fill=..level..), data=df,geom="polygon", alpha=0.2)+
  scale_fill_gradient(low = "yellow", high = "red")+theme(legend.position = "top")

#facet_wrap(~crime_year, ncol=2)+

CRime analsis by year

ggmap(NewYork) +
geom_point(data = df, aes(x = Longitude, y = Latitude), color = "red")+facet_wrap(~crime_year,ncol = 2)+theme(legend.position = "top")